A joint UT Austin/Cornell team has taught a machine learning system based on the free/open Torch library to correctly guess the content of pixellated or blurred redactions with high accuracy: for masked faces that humans correctly guess 0.19% of the time, the system can make a correct guess 83% of the time, when given five tries.
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Writing on Medium, AI researcher Kate Crawford (previously) and Simply Secure (previously) co-founder Meredith Whittaker make the case for a new scholarly discipline that "measures and assesses the social and economic effects of current AI systems."
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The Guardian's published a long excerpt from Cathy O'Neil's essential new book, Weapons of Math Destruction, in which O'Neil describes the way that shoddy machine-learning companies have come to dominate waged employment hiring, selling their dubious products to giant companies that use them to decide who can and can't work.
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If you've read Cathy O'Neil's Weapons of Math Destruction (you should, right NOW), then you know that machine learning can be a way to apply a deadly, nearly irrefutable veneer of objectivity to our worst, most biased practices.
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I've been writing about the work of Cathy "Mathbabe" O'Neil for years: she's a radical data-scientist with a Harvard PhD in mathematics, who coined the term "Weapons of Math Destruction" to describe the ways that sloppy statistical modeling is punishing millions of people every day, and in more and more cases, destroying lives. Today, O'Neil brings her argument to print, with a fantastic, plainspoken, call to arms called (what else?) Weapons of Math Destruction.

UC London's offering a tax-free stipend for UK/EU students to work on designing and evaluating new approaches for continuous authentication, based on a solid theoretical underpinning so as to give a high degree of confidence that the resulting decisions match expectations and requirements" as well as "ways to preserve user privacy by processing behavioural measurements on the user’s computer such that sensitive information is not sent to the online service." (Image: LordHarris, CC-BY-SA) (Thanks, William!)
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Ever since the Supreme Court ordered the nation's voting authorities to get their act together in 2002 in the wake of Bush v Gore, tech companies have been flogging touchscreen voting machines to willing buyers across the country, while a cadre computer scientists trained in Ed Felten's labs at Princeton have shown again and again and again and again that these machines are absolutely unfit for purpose, are trivial to hack, and endanger the US election system.
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In Lock It and Still Lose It—On the (In)Security
of Automotive Remote Keyless Entry Systems, a paper given at the current Usenix Security conference in Austin, researchers with a proven track record of uncovering serious defects in automotive keyless entry and ignition systems revealed a technique for unlocking over 100,000 million Volkswagen cars, using $40 worth of hardware; they also revealed a technique for hijacking the locking systems of millions of other vehicles from other manufacturers.
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Trump's algorithm is to say semi-random things until his crowd roars its approval, then he iteratively modifies those statements, seeking more and more approval, until he maxes out and tries a new tack.
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You could not ask for a clearer, easier-to-read, more informative guide to facial recognition and machine learning thank Adam Geitgey's article, which is the latest in a series of equally clear explainers on machine learning, aimed at non-technical people -- and if you are a programmer, he's got links to Python sample source and projects you can use to develop your own versions.
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James Newman's "Megaprocessor" is a giant "microprocessor" built on transistors and other discrete components that he soldered onto boards and wired together in frames that stand 2m high and run 10m long.
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Meredith from Simply Secure writes, "Artificial Intelligence is already with us, and the White House and New York University’s Information Law Institute are hosting a major public symposium to face what the social and economic impacts might be. AI Now, happening July 7th in New York City, will address the real world impacts of AI systems in the next next 5-10 years."
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Iain ("an ex-physicist currently working as a data scientist") scraped Dark Lyrics and built a dataset of lyrics to 222,623 songs by 7,364 metal bands, then used traditional natural language processing techniques to analyze them.
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A very good piece by Tom Simonite in the MIT Technology Review looks at the implications of Intel's announcement that it will slow the rate at which it increases the density of transistors in microprocessors.
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